Fusing Continuous-Valued Medical Labels Using a Bayesian Model

Annals of Biomedical Engineering

Volumn 43, Issue 12, 2015, Pages 2892-2902

  Zhu, Tingting ^a   Dunkley, Nic ^a   Behar, Joachim ^a   Clifton, David A ^a   Clifford, Gari D ^a,b,c  

^a UNIVERSITY OF OXFORD   (United Kingdom)

^b EMORY UNIVERSITY   (United States)

^c GEORGIA INSTITUTE OF TECHNOLOGY   (United States)

Author keywords

Bayes methods; Crowdsourcing; Electrocardiography; Time series analysis

Indexed keywords

ALGORITHMS; BAYESIAN NETWORKS; ELECTROCARDIOGRAPHY; MAXIMUM PRINCIPLE; MEAN SQUARE ERROR;

ACCURATE ESTIMATION; AUTOMATED ALGORITHMS; BAYES METHOD; CROWDSOURCING; EXPECTATION MAXIMIZATION; PRECISION AND BIAS; ROOT MEAN SQUARE ERRORS; TIME-SERIES MEDICAL DATA;

TIME SERIES ANALYSIS;

ACCURACY; ALGORITHM; ANALYTICAL ERROR; ARTICLE; BAYES THEOREM; CONTINUOUS VALUED MEDICAL LABEL; CROWDSOURCING; ELECTROCARDIOGRAM; HUMAN; INFORMATION PROCESSING; LONG QT SYNDROME; MEDICAL INFORMATION; PRIORITY JOURNAL; QRS COMPLEX; QT INTERVAL; SIMULATION; T WAVE; TIME SERIES ANALYSIS; ELECTROCARDIOGRAPHY; FACTUAL DATABASE; FEMALE; MALE; MIDDLE AGED; STATISTICAL MODEL;

ALGORITHMS; BAYES THEOREM; DATABASES, FACTUAL; ELECTROCARDIOGRAPHY; FEMALE; HUMANS; MALE; MIDDLE AGED; MODELS, STATISTICAL;

EID: 84945435017     PISSN: 00906964     EISSN: 15739686     Source Type: Journal    
DOI: 10.1007/s10439-015-1344-1     Document Type: Article

References (26)

1. Andrew, W., V. Michael, D. Jeff, G. M. Nair, C. Plater-Zyberk, L. Griffith, J. Ma, C. Zachos, M. L. Sivilotti. Variability of QT interval measurements in opioid-dependent patients on methadone. CJAM 2:10–16, 2014.
2. Bousseljot, R., D. Kreiseler, A. Schnabel. Nutzung der EKG-Signaldatenbank CARDIODAT der PTB uber das Internet. Biomed. Tech. 40:317–318, 1995.
3. Christov, I., I. Dotsinsky, I. Simova, R. Prokopova, E. Trendafilova, and S. Naydenov. Dataset of manually measured QT intervals in the electrocardiogram. Biomed. Eng. Online 5:31, 2006.
4. Clifford, G. D., F. Azuaje, and P. E. McSharry. Advanced Methods and Tools for ECG Analysis. Engineering in Medicine and Biology. Norwood, MA: Artech House, 2006
5. Couderc, J. P., C. Garnett, M. Li, R. Handzel, S. McNitt, X. Xia, S. Polonsky, and W. Zareba. Highly automated QT measurement techniques in 7 thorough QT studies implemented under ICH E14 guidelines. Ann. Noninvasive Electrocardiol. 16:13–24, 2011.
6. Dawid, A. P. and A. M. Skene. Maximum likelihood estimation of observer error-rates using the EM algorithm. Appl. Stat. J. R. Stat. Soc. C 28:20–28, 1979.
7. Dekel, O. and O. Shamir. Good learners for evil teachers. In: Proceedings of the 26th Annual International Conference on Machine Learning, ICML ’09, ACM, pp. 233–240, 2009.
8. Ehlert, F.A., J. J. Goldberger, J. E. Rosenthal, and A. H. Kadish. Relation between QT and RR intervals during exercise testing in atrial fibrillation. Am. J. Cardiol. 70:332–338, 1992.
9. Goldenberg, I., A. J. Moss, W. Zareba, et al.: QT interval: how to measure it and what is “normal”. J. Cardiovasc. Electrophysiol. 17:333–336, 2006.
10. Hughes, N. P. Probabilistic Models for Automated ECG Interval Analysis. Ph.D. Thesis, University of Oxford, 2006.
11. International Conference on Harmonization of Technical Requirements for Registration of Pharmaceuticals for Human Use: Guidance for Industry E14: Clinical Evaluation of QT/ QTc Interval Prolongation and Proarrhythmic Potential for Non-Antiarrhythmic Drugs, 2005. Available at: http://www.fda.gov/downloads/drugs/guidancecomplianceregulatoryinformation/guidances/ucm073153.pdf.
12. Malik, M., P. Frbom, V. Batchvarov, K. Hnatkova, and A. J Camm. Relation between QT and RR intervals is highly individual among healthy subjects: implications for heart rate correction of the QT interval. Heart 87:220–228, 2002.
13. Metlay, J.P., W. N. Kapoor, and M. J. Fine. Does this patient have community-acquired pneumonia?: Diagnosing pneumonia by history and physical examination. J. Am. Coll. Cardiol. 278:1440–1445, 1997.
14. Molinari, F., L. Gentile, P. Manicone, R. Ursini, L. Raffaelli, M. Stefanetti, A. D’Addona, T. Pirronti, and L. Bonomo. Interobserver variability of dynamic MR imaging of the temporomandibular joint. La Radiologia Medica 116:1303–1312, 2011.
15. Moody, G. B., H. Koch, and U. Steinhoff. The PhysioNet/Computers in cardiology challenge 2006: QT interval measurement. Comput. Cardiol. 33:313–316, 2006.
16. Raykar, V. C., S. Yu, L. H. Zhao, G. H. Valadez, C. Florin, L. Bogoni, and L. Moy. Learning from crowds. JMLR 11:1297–1322, 2010.
17. Salerno, S. M., P. C. Alguire, and H. S. Waxman, H.S.: Competency in interpretation of 12-lead electrocardiograms: a summary and appraisal of published evidence. Ann. Intern. Med. 138:751–760, 2003.
18. Valizadegan, H., Q. Nguyen, and M. Hauskrecht. Learning Medical Diagnosis Models from Multiple Experts. In: AMIA Annual Symposium Proceedings, pp. 921–930, 2012.
19. Viskin, S., U. Rosovski, A. J. Sands, E. Chen, P. M. Kistler, J. M. Kalman, L. R. Chavez, P. I. Torres, F. E. CruzF, O. A. Centurion, A. Fujiki, P. Maury, X. Chen, A. D. Krahn, F. Roithinger, L. Zhang, G. M. Vincent, and D. Zeltser. Inaccurate electrocardiographic interpretation of long QT: the majority of physicians cannot recognize a long QT when they see one. Heart Rhythm 2:569–574, 2005
20. Warby, S. C., S. L. Wendt, P. Welinder, E. G. Munk, O. Carrillo, H. B. Sorensen, P. Jennum, P. E. Peppard, P. Perona, and E. Mignot. Sleep-spindle detection: crowdsourcing and evaluating performance of experts, non-experts and automated methods. Nat. Methods 11:385–392, 2014.
21. Warfield, S. K., K. H. Zou, and W. M. Wells. Validation of image segmentation by estimating rater bias and variance. Philos. Trans. R. Soc. London A 366:2361–2375, 2008.
22. Welinder, P. and P. Perona. Online crowdsourcing: rating annotators and obtaining cost-effective labels. In: IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops, pp. 25–32, 2010.
23. Welinder, P., S. Branson, P. Perona, and S. J. Belongie. The multidimensional wisdom of crowds. Adv. Neural Inf. Process. Syst. 23:2424–2432, 2010.
24. Willems, J., P. Arnaud, J. van Bemmel, P. Bourdillon, C. Brohet, S. Dalla Volta, J. Andersen, R. Degani, B. Denis, M. Demeester et al. Assessment of the performance of electrocardiographic computer programs with the use of a reference data base. Circulation 71(3):523–534, 1985.
25. Zhu, T., J. Behar, T. Papastylianou, and G. D. Clifford. Crowdlabel: a crowd-sourcing platform for electrophysiology. Comput. Cardiol. 41:789–792, 2014.
26. Zhu, T., A. E. Johnson, J. Behar, and G. D. Clifford. Crowd-sourced annotation of ECG signals using contextual information. Ann. Biomed. Eng. 42:871–884, 2014.